Development of a Novel 2-Dimensional Micro-Heater Array Device with Regional Selective Heating
Bibliographic record
Abstract
This paper reports the development of a micro-heater array device that can be selectively heated at an arbitrary location. To confirm the heating characteristics of this micro-heater array device, heating experiments using a thermo-responsive gel were conducted. Since a micro-heater can supply heat with a rapid-response on a micro-scale, various applications have been studied. Based on these characteristics, micro-heaters have often been used in recent research applications involving biological cells. To expand the versatility of the micro-heater, the development of micro-heater array systems that can supply heat selectively at an arbitrary location is required. In this work, to support micro-heater applications in the field of biochemistry, the design and materials of a micro-heater array device were optimized and a fabrication process was established. Furthermore, the usefulness of this device was verified using a thermo-responsive gel, and control of the temperature distribution on a glass substrate was successfully demonstrated. This micro-heater array device can be heated with regional selectivity, and each region can be controlled to an arbitrary temperature, so the device is also capable of generating temperature gradients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".